Color Photometric Stereo for Multicolored Surfaces

We present a multispectral photometric stereo method for capturing geometry of deforming surfaces. A novel photometric calibration technique allows calibration of scenes containing multiple piecewise constant chromaticities. This method estimates per-pixel photometric properties, then uses a RANSAC-based approach to estimate the dominant chromaticities in the scene. A likelihood term is developed linking surface normal, image intensity and photometric properties, which allows estimating the number of chromaticities present in a scene to be framed as a model estimation problem. The Bayesian Information Criterion is applied to automatically estimate the number of chromaticities present during calibration. A two-camera stereo system provides low resolution geometry, allowing the likelihood term to be used in segmenting new images into regions of constant chromaticity. This segmentation is carried out in a Markov Random Field framework and allows the correct photometric properties to be u...

• Type: Journal
• Year: 2011
• Where: ICCV
• Authors: Robert Anderson, Bjorn Stenger, Roberto Cipolla
• Keywords: Bayesian Information Criterion, Calibration Technique, Computer Vision, Ground Truth Data, ICCV 2011